alirezadir / Production-Level-Deep-LearningLinks
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
☆4,596Updated 7 months ago
Alternatives and similar repositories for Production-Level-Deep-Learning
Users that are interested in Production-Level-Deep-Learning are comparing it to the libraries listed below
Sorting:
- A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dm…☆9,811Updated 2 years ago
- In this repository, I will share some useful notes and references about deploying deep learning-based models in production.☆4,379Updated last year
- Lab materials for the Full Stack Deep Learning Course☆1,219Updated 3 years ago
- 📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.☆2,878Updated 2 years ago
- A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)☆7,441Updated last year
- https://huyenchip.com/ml-interviews-book/☆4,455Updated 9 months ago
- ✍️ A carefully curated list of NLP paper summaries☆1,480Updated 4 years ago
- Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.☆3,640Updated 6 years ago
- This repo contains annotated research papers that I found really good and useful☆2,765Updated 3 weeks ago
- Full Stack Deep Learning Online Course☆911Updated 4 years ago
- A repo for data science related questions and answers☆2,427Updated 3 years ago
- This repository is to prepare for Machine Learning interviews.☆1,613Updated 6 years ago
- A curated list of references for MLOps☆13,533Updated last year
- Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.☆12,218Updated 2 years ago
- This repo is meant to serve as a guide for Machine Learning/AI technical interviews.☆7,489Updated last month
- Machine learning glossary☆3,108Updated last year
- PyTorch tutorials and best practices.☆1,709Updated 9 months ago
- A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning☆19,928Updated last week
- Learn how to design, develop, deploy and iterate on production-grade ML applications.☆3,280Updated last year
- Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.☆1,231Updated 2 years ago
- Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.☆2,562Updated 4 years ago
- Top 200 deep learning Github repositories sorted by the number of stars.☆1,746Updated last year
- Data science interview questions and answers☆9,682Updated 2 months ago
- Answers to 120 commonly asked data science interview questions.☆3,825Updated 2 years ago
- Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources o…☆1,631Updated 2 months ago
- A collection of various deep learning architectures, models, and tips☆17,349Updated last year
- Natural Language Processing Best Practices & Examples☆6,444Updated 3 years ago
- Debugging, monitoring and visualization for Python Machine Learning and Data Science☆3,464Updated 3 months ago
- A Code-First Introduction to NLP course☆3,478Updated 2 years ago
- Source code accompanying O'Reilly book: Machine Learning Design Patterns☆2,052Updated 4 years ago